Build Smarter AI Apps: Memory, Tools, Retrieval & Structured Output with Python, Pydantic & Ollama

Full-text tutorial with source code (requires MLExpert Pro): https://www.mlexpert.io/v2-bootcamp/ai-engineer-toolkit

Want to build AI applications that solve real problems? This tutorial shows you how to enhance LLMs with memory for context awareness, structured outputs for reliable data, tool integration for performing actions, and retrieval for accessing external knowledge. All of this is implemented locally with Python and Ollama!

"Building effective agents" blog post: https://www.anthropic.com/research/building-effective-agents

AI Bootcamp: https://www.mlexpert.io/
LinkedIn: https://www.linkedin.com/in/venelin-valkov/
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Discord: https://discord.gg/UaNPxVD6tv
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GitHub repository: https://github.com/curiousily/AI-Bootcamp

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00:00 - Welcome
00:39 - The super (augmented) LLM
02:07 - Full-text tutorial and source code on MLExpert.io
02:44 - Memory
05:32 - Structured output
10:46 - Tools (function calling)
22:38 - Retrieval
28:43 - Conclusion

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#artificialintelligence #python #pydantic #ollama #rag #aiagents #chatgpt